Angular multi-variable analysis method for eliminating spectral multiplicative random error
A technology of multiplicative random error and multivariate analysis, applied in the direction of color/spectral characteristic measurement, etc., can solve the problems of quantitative accurate interference, multiplicative error, and EMSC method infeasibility, and achieve the goal of eliminating multiplicative error and avoiding interference Effect
Inactive Publication Date: 2014-06-04
GUANGXI UNIVERSITY OF TECHNOLOGY
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Problems solved by technology
Multiplicative errors lead to changes in signal amplitude. Under the premise of equal variance distribution, standard normal variable correction (SNV) and multiple scatter correction (MSC) methods are usually used to correct; in the case of different signal variances, extended multiple scatter can be used. Correction (EMSC) method correction, but requires prior knowledge support
[0006] In most cases, the signal variance varies with the intensity, which cannot meet the constraints of SNV and MSC, and often due to the lack of sufficient or accurate prior knowledge, the EMSC method is not feasible
In real-time and on-site measurements of spectra, intensity disturbances and particle scattering disturbances are common, resulting in multiplicative errors that directly interfere with quantitative accuracy
Method used
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Embodiment 1
[0084] The Raman spectrometer was selected to measure the carbon tetrachloride content in the mixture as an example.
[0085] 1) Spectral signal acquisition
[0086] In the multi-component mixture, carbon tetrachloride is added at a content of 2.5% to 25%, and carbon tetrachloride is added at ten equal intervals to prepare 5 groups of 50 series of samples, each of which contains 10 samples with a content of 2.5% to 25%. The concentration of other components in the sample is not relevant.
[0087] By determining the measurement distance and integration time of each sample, the multiplicative disturbance in the measurement signal is formed, and the Raman spectrum signal of a series of samples is collected, such as Figure 4 Shown.
[0088] 2) Direct PLS modeling
[0089] From 50 samples, a total of 15 samples with 3 concentrations are randomly selected from each group as the modeling correction set, and the partial least squares modeling is directly performed. Confirm that the number of...
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The invention discloses an angular multi-variable analysis method for eliminating a spectral multiplicative random error. The method comprises the steps of modeling and prediction. A direct processing method based on a spectral intensity signal is replaced with an angular multi-variable conversion method, so that a multiplicative error of the signal is eliminated, and the influence of disturbance on the signal intensity of a system is avoided.
Description
Technical field: [0001] The invention relates to an angular multivariate analysis method for eliminating random errors of spectral multiplication. Background technique: [0002] In spectral analysis, the acquired spectral signal is interfered by a variety of random errors, especially the reflection measurement methods often used in Raman and near-infrared, not only by common noise and baseline drift and other superimposition errors, but also by scattering and reflection optical path Interference of equal multiplicative error. [0003] In a system where the measured value (x) and the response signal (y) have a linear relationship, the additive (e a ) And multiplicative (e m ) Two types of errors can be expressed as: [0004] y=e m ·A·x+e a (1) [0005] The additive error causes the overall signal fluctuation and deflection, but does not affect the amplitude of the signal. It can be better eliminated by using background subtraction or differentiation (differential) methods. The mu...
Claims
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Inventor 姚志湘粟晖
Owner GUANGXI UNIVERSITY OF TECHNOLOGY